{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[19.81405274 17.578125   16.58886617 15.01219741]\n"
     ]
    }
   ],
   "source": [
    "from numpy import*\n",
    "t=array([52,45,43,32])\n",
    "s=array([1.62,1.60,1.61,1.46])\n",
    "z=t/s**2\n",
    "print(z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0. 0. 0.]\n",
      "[1. 1. 1. 1.]\n",
      "[0 1 2 3 4]\n"
     ]
    }
   ],
   "source": [
    "from numpy import*\n",
    "a=zeros(3)\n",
    "print(a)\n",
    "b=ones(4)\n",
    "print(b)\n",
    "c=arange(5)\n",
    "print(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 6.  1.  5.  5.  7.  1.  7. 49.  2. 10. 15. 12.  3. 10.  8. 48.  1. 92.]\n"
     ]
    }
   ],
   "source": [
    "from numpy import*\n",
    "a=loadtxt(\"test.txt\")\n",
    "b=a.sum(1)\n",
    "print(b)\n",
    "savetxt(\"总分.txt\",b,fmt='%.2f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "b.shape=(18,1)\n",
    "c=hstack((a,b))\n",
    "savetxt(\"总分2.txt\",c,fmt='%.2f',delimiter='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.pyplot import*\n",
    "a=[1,4,5,5]\n",
    "pie(a)\n",
    "show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.pyplot import*\n",
    "a=[1,4,5,5]\n",
    "rcParams['font.sans-serif']=['SimHei']\n",
    "labels=['不及格','及格','良好','优秀']\n",
    "colors=['red','blue','yellow','green']\n",
    "pie(a,colors=colors,labels=labels)\n",
    "title('学生体质健康分布图')\n",
    "show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy\n",
    "a=numpy.loadtxt(\"test.txt\")\n",
    "from matplotlib.pyplot import*\n",
    "plot(a)\n",
    "rcParams['font.sans-serif']=['SimHei']\n",
    "legend(labels=['金牌','银牌','铜牌'])\n",
    "colors=['red','blue','yellow','green']\n",
    "title('奖牌图')\n",
    "show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXgAAAD2CAYAAADcUJy6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAJ70lEQVR4nO3dYajdd33H8c/XljKppU1ICLga40CfTCcrYVqwI3vQTinbgz1YB64DtQSH4ANBZlEI1ELbgYFNsDSjG3kgQhWcsFjoGOvMoB0kUseYDp9UiqwUV9cQfDLKdw/uCbS39zY35557b/LN6wUl/Z/zP//zO/y4b/75/8/vpro7AMzzjr0eAAA7Q+ABhhJ4gKEEHmAogQcY6sa9HsAlBw4c6CNHjuz1MACuKefPn/9Fdx/c6LmrJvBHjhzJuXPn9noYANeUqvrZZs+5RAMwlMADDCXwAEMJPMBQAg8wlMADDLWlwFfVoao6u/j/W6vq6ap6pqq+W1U3VdW+qvp+VZ2rqicW+72vqs5U1dmq+tpOfggA3uqyga+qfUlOJ7l58dAnk5zs7nuSvJzk40nuT/LN7j6a5JaqOprksSRf7e67ktxeVcd2YPwAbGIrC51eT3Jfku8lSXd/4w3PHUzySpJbknywqm5L8p4kLyX5QJIfLvZ7JcmtKxozAFtw2cB394Ukqao3PV5VdybZ193PV9V/J7k3yeeT/DjJq0m+k+REVT2ftbP8B9cfu6qOJzmeJIcPH97WBwFmOPKlM3s9hF334qP37shxl7rJWlX7k3w9yacXD51I8tnufijJT5J8qrsfTvJ0kgeSnO7ui+uP092nuvtodx89eHDDX6UAwJKuOPBVdVOSbyd5sLsv/Q6EfUk+VFU3JPlIkkv/DuALSQ4nObmCsQJwBZY5g/9MkjuSfLmqnq2q+5I8kuRUkteS7E/yrcW+X8zaDdlfrWKwAGzdln+bZHcfW/z5eJLHN9jlNzd4zYmlRwbAtljoBDCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQwk8wFACDzCUwAMMJfAAQ60s8FW1v6rurqoDqzomAMvbUuCr6lBVnX2b7X1J/iHJ7yT556o6uHj8yap6rqq+suJxA3AZN15uh0W8Tye5eaPthd9K8oXufn7x/B1VdXOSG7r7zqr626p6f3f/dPUfAYCNXDbwSV5Pcl+S722yne7+lySpqt/N2ln8Q0keTvLUYpdnknwsyZsCX1XHkxxPksOHDy/7GbhOHPnSmb0ewq578dF793oIXMMue4mmuy9092ubbV9SVZW18P8yyf9l7Qz/54unX01yaINjn+ruo9199ODBg0t+BAA2srKbrL3mc0n+PckfJrmY5J2Lp9+1yvcC4PJWEt2q+ouq+rPF5m1J/jfJ+axdlkmSDyd5cRXvBcDWbOUa/FacSvJUVT2Q5D+yds39liRnq+rdST6R5KMrei8AtmDLge/uY5ttd/cvk9y97iUXqurY4vG/3Oi6PQA7Z1Vn8BtahP+py+4IwMq58QkwlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAEMJPMBQAg8wlMADDCXwAENdceCral9Vfb+qzlXVE1X1vqo6U1Vnq+prb9jvyap6rqq+stohA7AVy5zB35/km919NMktSZ5M8tXuvivJ7VV1rKr+KMkN3X1nkt+oqvevbsgAbMWNS7zmf5J8sKpuS/KeJAeS/HDx3CtJbk1yLMlTi8eeSfKxJD9df6CqOp7k+GLzYlX91xLj2WsHkvxirwfBjtuTea7Hdvsdr2t79rO8zXl+76bH7e4rG0jVe5M8kuQnSW5P8lKSX0vyfJKTSX47yV8l+evu/lFV3ZPkju5+dLmxX92q6tzibzMMZp7nmzjHy5zBn0jy2e6+UFVfSHIxyX8m+WKS0919saouJnnnYv93xc1cgF23THj3JflQVd2Q5CNJOskLSQ5n7Qw+Sc5n7bJMknw4yYvbGyYAV2qZM/hHkvxd1q77PJfkW1k7ez/Z3b9a7PP3Sc5W1buTfCLJR1cw1qvVqb0eALvCPM83bo6v+Br8lg9ctS/J3Ul+0N0v78ibALCpHQs8AHvLzU+AoQR+E1V1a1U9XVXPVNV3q+qmjVbnVtWhqjr7hu0/r6pnF/+9UFVP7M0nYCu2Mc9vWtG9N6Nnq7Yxzxuu1L9WCPzmPpm1G8f3JHk5yZ9k3ercxX2G00luvvSi7n68u49197EkZ5P8ze4PnSuw1Dxn3Yruqhr1/emBlp3nx7Jupf4uj3tbBH4T3f2N7v7HxebBJH+at67OfT3JfUkurH99Vf16kkPdfW4XhsuStjHP61d0v7Q7I2YZ25jnD+StK/WvGQJ/GVV1Z9a++/9Skp8vHn41a/G+0N2vbfLSzyV5fBeGyAosMc//mrWvCn8+yY8X+3KVW2Kev5PkRFX9QZKPJ/mnXRvsCgj826iq/Um+nuTTWVuxu6XVuVX1jiS/l+TZHR4iK7DkPF9a0f1Q1n5tx6d2epxszzLz3N0PJ3k6yQNZrNTfhaGujMBvoqpuSvLtJA92989yZatz70ryb+07qFe9bczzRiu6uUpt8+d5/Ur9a4bAb+4zSe5I8uWqejZJJbm/qk4m+eMkZ97mtb+f5Ac7PkJWYdl5fiRrKx9fS7I/ayu6uXpt5+d5/Ur9a4aFTlfA6tzrg3m+PlwP8yzwAEO5RAMwlMADDCXwAEMJPMBQAg8w1P8Dk5tAVKog6E8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.pyplot import*\n",
    "bar(['2017','2018','2019'],['890','1130','1289'],width=0.5)\n",
    "show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
